Introduction To Empirical Methods for Policy Analysis

This section of IEM emphasizes how modern computer-intensive techniques and subjectivist (Bayesian) conceptions of probability are changing the way we think about applied statistics and decision making.  The motivation for this is the conviction that these perspectives offer a far simpler path to understanding what we mean by risk, uncertainty, and inference than do conventional textbook treatments of these topics.  This section of IEM assumes that you have a basic familiarity with differential calculus, simple descriptive statistics (means, medians, modes, standard deviations, etc), and the rudiments of probability.  It also assumes that you are comfortable with elementary algebra (ie, that at the very minimum you know how to interpret an intercept and a slope coefficient in a linear mathematical expression) and are able – or at least eager to learn – to work with symbolic notation (eg, summation and product operators, subscripts, elements of the Greek alphabet, etc).  If you are uncomfortable with these modes of abstract thinking, this may not be the appropriate section of IEM for you.


There is no required textbook.  The assigned readings are either posted on UT's electronic Canvas learning system or handed out in class.

Requirements and Expectations:

Students are evaluated in terms of their performance on homework assignments, occasional “Thought Pieces”, classroom discussion, one or two short empirical miniprojects, a midterm, and a final exam.